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Article

Structural Analysis and Functional Prediction of Gut Microbiota in Wild and Cultured Striped Knifejaw (Oplegnathus fasciatus)

by
Kai Zhu
1,2,3,
Susu Zhang
4,
Kaida Xu
1,2,3,* and
Haozhan Wang
5,*
1
Zhejiang Marine Fisheries Research Institute, Zhoushan 316000, China
2
Scientific Observing and Experimental Station of Fishery Resources for Key Fishing Grounds, Ministry of Agriculture and Rural Affairs of the People’s Republic of China, Zhoushan 316021, China
3
Key Laboratory of Sustainable Utilization of Technology Research for Fishery Resources of Zhejiang Province, Zhoushan 316021, China
4
School of Fishery, Zhejiang Ocean University, Zhoushan 316022, China
5
Sansha Marine Environmental Monitoring Center Station, State Oceanic Administration, Haikou 570100, China
*
Authors to whom correspondence should be addressed.
J. Mar. Sci. Eng. 2024, 12(12), 2275; https://doi.org/10.3390/jmse12122275
Submission received: 23 October 2024 / Revised: 3 December 2024 / Accepted: 7 December 2024 / Published: 11 December 2024
(This article belongs to the Section Marine Biology)
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Abstract

:
Understanding the role of gut microbiota in fish health is crucial for optimizing aquaculture practices and ensuring sustainable fish populations. In this study, the diversity and compositional differences of intestinal microbiota were comparatively analyzed between wild and cultured striped knifejaw (Oplegnathus fasciatus Kroyer, 1845). Using high-throughput 16S rDNA sequencing and bioinformatics, an in-depth investigation of the gut microbiota in both populations was conducted. The results revealed that the number of intestinal bacterial sequences was significantly higher in the cultured population than in the wild population. The study included 16 individuals from the wild population and 38 individuals from the cultured population, with an average weight of 67.7 ± 12.4 g and 44.9 ± 16.8 g, respectively. Alpha diversity analysis indicated that intestinal microbiota species richness and diversity were both greater in the cultured O. fasciatus. Furthermore, significant differences were observed in the intestinal bacterial communities between the two populations, with Pseudomonadota, Verrucomicrobia, and Bacillota dominating in the cultured population, whereas Pseudomonadota overwhelmingly dominated in the wild population. Functional prediction analysis revealed differences between the intestinal microbiota in pathways related to genetic and environmental information processing, as well as metabolism. This study provides critical data for understanding the structure and function of intestinal microbial communities in O. fasciatus and offers a theoretical foundation for optimizing farming strategies to improve fish health and growth performance.

1. Introduction

The intestine, a crucial organ for digestion and nutrient absorption in fish, hosts a microbial community dominated by Bacillota, Bacteroidota, Pseudomonadota, and Fusobacteria [1]. These microorganisms, primarily originating from the environment or feed, form a complex microecosystem with the host and its aquatic habitat. Studies have shown that gut microbiota markedly impact fish physiology, including nutrient absorption, metabolism, and immunity, directly influencing fish health [2,3,4,5]. Enzymes secreted by intestinal microbiota aid in food digestion and enhance nutrient absorption, and the antibiotic-like substances they produce prevent pathogenic microorganism invasion. Thus, understanding the structure of intestinal microbiota offers valuable insights for mitigating fish diseases.
Traditional research methods, such as culture isolation, denaturing gradient gel electrophoresis (DGGE), and randomly amplified polymorphic DNA analysis [6,7,8,9], have provided initial insights into gut microbiota structure. However, their limitations in identifying low-abundance microorganisms may lead to incomplete or inaccurate findings. In recent years, given the maturation and widespread application of MiSeq high-throughput sequencing, with its precision in analyzing microbial community structure [10,11,12], this method has become the leading technique used in gut microbiota studies. Compared with older methods, such as DGGE, high-throughput sequencing allows for the faster, more accurate analysis of complex gut microbiota samples and identifies low-abundance and nonculturable bacterial species [13,14]. This technology provides new perspectives for understanding the nutritional evolution between the host and gut microorganisms [10,11,12].
Studies have indicated that fish gut microbiota composition is primarily influenced by habitat and diet [15]. Therefore, compared with wild populations, the diversity of gut microbiota in cultured fish is affected by the aquaculture environment and feed. For instance, prior research has revealed variations in gut microbiota composition and abundance between wild and cultured environments for various species, including Coreius guichenoti (Sauvage, 1878), Onychostoma macrolepis (Bleeker, 1860), and Scophthalmus maximus (Linnaeus, 1758) [16,17,18]. In marine cage aquaculture, overfeeding-related digestive issues and enteritis are common, severely impacting profitability and fish health. Comparative analysis of gut microbiota in wild and cultured fish can provide insights for scientific, standardized disease prevention and control in aquaculture and informs the development of feed additives, such as probiotics.
Striped knifejaw (Oplegnathus fasciatus) of the family Oplegnathidae, also known as the barred knifejaw, is a warm-temperate coastal fish widely distributed in the Yellow Sea and East China Sea, China, as well as in waters south of Hokkaido, Japan. This species holds high edible and ornamental value. It primarily inhabits near-shore rocky reefs at depths of 15–100 m, making conventional trawling methods challenging. In Zhejiang’s coastal regions, angling and gill netting are the primary capture methods, although yields remain relatively low compared with market demand. Therefore, advances in large-scale reproduction techniques are essential for increasing O. fasciatus production, highlighting the importance of further aquaculture technology development.
Given the critical role of gut microbiota in fish nutrition, immunity, and disease prevention, a comprehensive comparative analysis of the gut microbiota structure between wild and cultured O. fasciatus populations is vital for facilitating the development of probiotics, other microbial ecological preparations, and feed formulations, while also offering insights for effective disease prevention and control. In this context, the present study employs high-throughput sequencing to analyze the 16S rRNA sequences of gut microorganisms from both wild and cultured O. fasciatus populations. By comparing species composition and diversity between these groups, we aimed to deepen our understanding of the ecological characteristics of gut microbiota in these populations. In the realm of O. fasciatus aquaculture, our findings provide a foundation for optimizing aquaculture management, mitigating disease incidence, and promoting fish health. Additionally, we have undertaken the comprehensive functional prediction of the gut microbiota, with the resultant insights providing invaluable practical direction for the scientific formulation of artificial feeds and the strategic utilization of probiotics.

2. Materials and Methods

2.1. Sample Collection and Processing

Wild O. fasciatus samples were collected from the Zhoushan Sea (30°10′–30°45′ N, 122°8′–122°50′ E) (Figure 1) using gillnets and manual fishing methods. To ensure prompt capture, gillnets were deployed in the morning and retrieved the same afternoon. Owing to the close proximity of the fishing grounds to the shoreline, the specimens were immediately preserved on ice and transported to the laboratory to maintain their freshness. From this pool of freshly caught specimens, 100 individuals were randomly selected for subsequent analysis. Upon arrival at the laboratory, these selected specimens were swiftly dissected to extract their intestinal tissue, which was then processed for gut microbiota analysis. Cultured O. fasciatus population samples were obtained from two distinct ponds at the Xixuan Fisheries Science and Technology Island experimental facility. A total of 74 individuals were chosen (Table 1), with 37 randomly selected from each pond, ensuring a balanced and representative sample size for subsequent analyses. Live fish were anesthetized via eugenol (40 mg/L) [19] (Zhengzhou Can Biotechnology Co., Ltd., Zhengzhou, China; 99% purity) immersion, rinsed with 75% ethanol (Sinopharm Chemical Reagent Co., Ltd., Shanghai, China; 99% purity), and dissected under sterile conditions. Intestinal contents were extracted, with dissected samples numbered and stored at −2 °C for DNA extraction. The culturing facilities, environment, and feeding methods followed the artificial culturing techniques for O. fasciatus described by Sun et al. [20].

2.2. DNA Extraction and Determination of Intestinal Microbial Diversity

DNA was extracted from the samples obtained from 16 randomly chosen individuals belonging to the natural population and 39 individuals (19 and 20 from each of the two culture ponds, respectively) from the cultured population, out of a total of 100 and 74 specimens, respectively, using the Power Food Microbial DNA Isolation Kit (QIAGEN Srl, Milano, Italy), following the manufacturer’s instructions. The quality and concentration of DNA were assessed using 1.2% agarose gel electrophoresis and a Qubit 4 fluorometer (Thermo Fisher Scientific, Waltham, MA, USA).
The V3–V4 region of the bacterial 16S rRNA gene was amplified using primers 341F (ACTCCTACGGGAGGCAGCAG) and 806R (GGACTACHVGGGTATCTAAT) (http://www.arb-silva.de (accessed on 15 May 2023)). PCR amplification was performed using an rTaq DNA Polymerase 20 μL reaction system comprising 2 μL of 10× buffer, 2 μL of 2.5 mmol/L dNTPs, 0.8 μL of each primer (341F/806R), 0.2 μL of Taq enzyme, 0.2 μL of bovine serum albumin, 10 ng of template DNA, and ddH2O adding up to 20 μL. The reaction conditions were as follows: initial denaturation at 95 °C for 3 min, followed by 30 cycles of denaturation at 95 °C for 45 s, annealing at 56 °C for 45 s, and extension at 72 °C for 45 s, with a final extension at 72 °C for 10 min. The amplified products were separated using 2% agarose gel, extracted using the AxyPrep DNA Gel Extraction Kit (Axygen Biosciences, Union City, CA, USA) according to the manufacturer’s instructions, and quantified using the Qubit 4 fluorometer. The purified products were pooled in equimolar amounts and sequenced on the Illumina HiSeq 2500 platform for a total of 55 samples, which included the 16 natural population and 39 cultured population individuals, following the instructions provided by Igene Code Biotechnology Co., Ltd. (Beijing, China)

2.3. Data Processing Methods

2.3.1. Operational Taxonomic Unit (OTU) Clustering and Species Annotation

Paired-end sequence data were obtained for all samples using barcodes. Pandaseq (V2.11) and PRINSEQ (V0.20.4) software were used to optimize the data through read merging, quality control, filtering, and sequence denoising [21]. The amplicon sequence variant (ASV) representative sequences and abundance information were obtained. ASV clustering and species taxonomic analyses were then performed. Various diversity indices were analyzed based on the ASV clustering results, and QIIME2 (2021.11) software was employed to compare and annotate them with the Silva database at different taxonomic levels to obtain species classification information for each OTU [22,23].

2.3.2. Alpha Diversity

Bacterial abundance was calculated using the observed_features, Chao1 (Schao1), and ACE (Sace) indices. Bacterial diversity was calculated using the Simpson dominance (D) and Shannon diversity (H’) indices, whereas the good_coverage (C) metric was employed to assess sequencing depth [24,25,26].
S obs   =   Actual   number   of   OTUs   measured
S chao 1 = S obs n 1 n 1 − 1 2 n 2 + 1
S ace = S abund + S rare C ace + n 1 C ace γ ace 2
D simpson = ∑ i = 1 S obs n i n i − 1 N N − 1
H shannon ′ = − ∑ i = 1 S obs n i N ln ⁡ n i N
C = 1 − n i N
In the listed formulas, n1 represents the number of OTUs containing only one sequence (singletons), n2 represents OTUs with exactly two sequences, and ni represents OTUs with i sequences, where N is the total number of sequences in the sample. Sabund denotes OTUs with >10 sequences, whereas Srare denotes OTUs with <10 sequences. Cace indicates the proportion of non-singleton species among all low-abundance (≤10 occurrences) species, and γace2 represents the coefficient of variation.

2.3.3. Statistical Analysis

R 3.3.1 software was employed for species composition analysis. R tools were also used to create and analyze rarefaction curves, composition analysis plots, and Venn diagrams. The Wilcoxon rank sum test was applied to compare alpha diversity indices between groups, and the ANOSIM test was used to assess structural differences in intestinal microbiota between the wild and cultured populations, with p < 0.01 indicating significant differences [16,17,18]. The PICRUSt tool, which predicts microbial metabolic functions, was used to normalize the OTU abundance table. Clusters of Orthologous Groups and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional annotations were assigned to the OTUs based on their corresponding Green GeneIDs, yielding functional annotation and abundance information across the samples [21].

3. Results

3.1. Alpha Diversity of Gut Microbiota

The 16S rDNA sequence counts of gut bacteria varied between the wild and cultured O. fasciatus populations. The cultured population exhibited sequence counts of 88,466–159,235, with an average of 121,394 reads, whereas the wild population displayed sequence counts of 71,826–116,821, with an average of 96,791 reads. Both populations revealed high coverage values exceeding 88%, ensuring reliable microbial diversity analysis. When sequencing counts were <10,000, the OTU numbers (based on the Chao1 index) increased rapidly with sequencing depth. However, above 20,000 sequences, the Chao1 index curve stabilized, indicating sufficient sequencing depth to capture the microbial community composition and diversity.
Further analysis revealed that the number of ASVs in the guts of cultured O. fasciatus was significantly higher than that in the guts of their wild counterparts. Venn diagram analysis revealed 1262 genera common to both populations, with 617 unique to the cultured population and 225 unique to the wild population. Alpha diversity index analysis of the ASV counts demonstrated significant differences between the groups (Figure 2). The Ace, Chao, and faith_pd indices were significantly higher in the cultured population than in the wild population (p < 0.01), indicating greater gut microbiota species richness. Additionally, the Shannon and Simpson indices were higher in the cultured population, confirming greater microbial diversity.

3.2. Composition of Gut Microbiota

The gut bacteria of both populations exhibited high diversity, covering 56 phyla, 158 classes, 380 orders, 608 families, 1262 genera, and 552 species. Moreover, significant differences in bacterial communities were observed between the two populations (Table 2, Figure 3).
In the cultured population, the dominant bacterial phyla included Pseudomonadota (28.4%), Verrucomicrobiota (23.7%), Bacillota (21.4%), and Chloroflexota (5.6%) (Table 2, Figure 3). At the family level, Akkermansiaceae (22.9%), Enterobacteriaceae (12.5%), and Enterococcaceae (10.9%) were predominant, with Akkermansia (25.93%), Enterococcus (10.93%), and Escherichia-Shigella (6.73%) showing high abundances at the genus level (Figure 4, Figure 5).
In contrast, the wild population was dominated by Pseudomonadota (86.3%), followed by Bacillota (9.0%) and Bacteroidota (2.4%) (Table 2, Figure 3). At the family level, Vibrionaceae was predominant, comprising 66.0% (Figure 4). Notably, certain genera, including Photobacterium (57.80%), Psychrobacter (7.65%), Lactobacillus (6.12%), and Vibrio (4.67%), were found to be relatively abundant in the samples from the wild population (Figure 5). Specifically, species such as Photobacterium leiognathi, Photobacterium damselae, Psychrobacter cibarius, Psychrobacter maritimus, Lactobacillus pontis, and Lactobacillus panis exhibited significantly higher relative abundances in the wild population than in the cultured population.

3.3. Nonmetric Multidimensional Scaling Analysis of Gut Microbiota

In nonmetric multidimensional scaling (NMDS) analysis, a stress value below 0.05 indicates strong representativeness, suggesting that the graph accurately reflects community distribution. NMDS results showed differences in gut microbial composition between populations, with variations among individuals. Notably, differences between populations were greater than those among individuals within the same population over the same period. Furthermore, the gut microbiota of the wild population was more clustered, whereas that of the cultured population was more dispersed (Figure 6).

3.4. Functional Prediction of Gut Microbiota

KEGG pathway analysis predicted that the gut microbiota of O. fasciatus contains numerous genes involved in essential metabolic functions. These genes were found to be related to six major metabolic pathways at the primary functional level, with genetic information processing (Figure 7), environmental information processing, and metabolism being the most prominent. In wild O. fasciatus, functional gene expression for genetic information processing and metabolism was significantly lower than that in the cultured population, whereas it was relatively higher for cellular processes, environmental information processing, human diseases, and organismal systems.
At the secondary functional level, we identified 42 metabolic functions, 15 of which had an abundance exceeding 1% (Figure 8). Compared with the cultured population, the wild population exhibited significantly increased metabolic functions in carbohydrate metabolism, xenobiotics biodegradation and metabolism, membrane transport, metabolism of other amino acids, signal transduction, cell motility, and infectious diseases. Conversely, metabolic functions related to nucleotide metabolism, replication and repair, translation, glycan biosynthesis and metabolism, energy metabolism, and metabolism of cofactors and vitamins were relatively lower, along with those involving bacterial cell growth and death, as well as folding, sorting, and degradation.
Further phenotypic classification and intergroup difference analysis of the O. fasciatus gut microbial communities revealed that the wild population exhibited a significantly higher frequency of stress tolerant, potentially pathogenic, Gram-negative, biofilm-forming, facultatively anaerobic, and mobile elements traits compared with that of the cultured population but a relatively lower frequency of Gram-positive, aerobic, and anaerobic traits (Figure 9).

4. Discussion

In this study, high-throughput sequencing was employed to analyze the intestinal microbial communities of both wild and cultured O. fasciatus populations. The results revealed significant differences in microbiota composition between these populations, likely influenced by ecological environment, diet, and farming practices. Dietary disparities, with cultured fish receiving a stable diet and wild fish a diverse diet, contribute to these variations. Previous research indicated that diet [27,28] and host species [29,30] are crucial factors shaping fish intestinal microbiota. The habitat environment, differing in regards to water quality and ecological conditions, also plays a key role. Additionally, ecological succession at the wild fish sampling site impact microbiota diversity.
In natural environments, intestinal microbiota diversity is influenced by food sources and environmental changes, showing substantial variability. Principal coordinates analysis of beta diversity revealed significant differences in microbiota structure between the wild and cultured populations, likely due to their differing environments and diets. Cultured populations typically receive stable artificial feed, whereas wild populations may consume a broader range of food sources, including small aquatic organisms and algae, leading to distinct microbiota compositions. Alpha diversity analysis showed lower microbial richness and diversity in the wild population compared with the cultured population. This aligns with studies of cultured koi carp [31] and multiscale, white-scaled fish [16], where higher microbial richness and diversity were observed in cultured samples. This difference may be due to the stable, nutritious feed provided in artificial environments, which promotes microbial growth. However, some studies, such as those in turbot [1], suggest that wild animals may have a higher intestinal microbial diversity, linked to specific ecological conditions and host species. Habitat environment also markedly influences intestinal microbiota composition in wild and cultured populations. Previous research has emphasized the dominant role of host habitat in structuring wild fish microbiota [32]. Although both populations were sampled from the same sea area, the cultured population’s water underwent anthropogenic purification, leading to differences in microorganism types and quantities compared with those of the natural sea, likely impacting the intestinal microbiota of cultured fish. Conversely, the sampling site for the wild population is situated at the confluence of the Yangtze River and the East China Sea, where the distinctive ecological environment may trigger ecological succession in microbial communities [33], ultimately resulting in a decrease in gut microbiota diversity within the wild population. Additionally, the timing of sample collection (autumn) may also play a role, as the elevated environmental temperatures experienced by cultured populations compared to wild populations during this season could potentially stimulate an increase in diversity, as evidenced in studies that have compared the intestinal microbiota of wild and cultured Sebastes schlegelii [34].
In terms of species composition, both Pseudomonadota and Bacillota were highly abundant in both populations, highlighting their functional importance to the host. Pseudomonadota are closely associated with the marine environment, and their abundance is linked to host health. Bacillota help regulate the host’s energy balance [35]. Previous studies have confirmed the dominance of Pseudomonadota and Bacillota in marine fish gut microbiota [36,37,38], consistent with our findings. These bacterial phyla play key roles in the gut microbiota of several fish species, including Plectropomus leopardus (Lacepède, 1802), Oncorhynchus mykiss (Walbaum,1792), Rachycentron canadum (Linnaeus, 1766), Lates calcarifer (Bloch,1790), Trachinotus blochii (Linnaeus, 1758) [39,40,41,42,43], Nibea albiflora and Nibea diacanthus [29], Megalobrama terminalis [35], Micropterus salmoides (Lacépède, 1802) [28], and Symphysodon haraldi (Schultz, 1960) [44]. In our study, Pseudomonadota abundance was significantly higher in the wild population, whereas Bacillota, Verrucomicrobia, and several other phyla were significantly less abundant in this population. The elevation of Proteobacteria within the host’s intestinal microbiome constitutes a ubiquitous hallmark in individuals afflicted with viral or pathogenic bacterial infections, and this notable attribute may be considered as a potential diagnostic indicator of ecological imbalance and disease manifestation within the animal’s gut environment [45,46].
At the genus level, our analysis revealed specific differences in gut microbiota between the wild and cultured populations. The differential enrichment of certain bacterial groups under varying feeding conditions likely reflects their functional roles [47,48,49]. For instance, Photobacterium, more abundant in the wild population, is known for producing polyunsaturated fatty acids (PUFAs) [50]. Unlike the cultured population, which obtains PUFAs from feed, the wild population may rely more on such bacterial groups for essential PUFA synthesis. Certainly, in comparison to the cultured population, the wild population demonstrated a notably higher relative abundance of Pseudomonas. A significant proportion of Pseudomonas species are known to possess the capacity to catabolize fats within the substrate, subsequently producing fatty acids, aldehydes, ketones, and an array of additional compounds [51]. Similar findings, such as the high abundance of Cetobacterium in the gut of Epinephelus coioides, which produces vitamin B12 and benefits glucose homeostasis in fish [52,53], have been reported in other studies. Conversely, bacterial genera associated with the aquaculture environment and feed components, such as Escherichia-Shigella, were more abundant in the cultured population. Escherichia-Shigella exerts a crucial function in the metabolism of amino acids derived from animal protein feeds [54]. In contrast to the wild population of O. fasciatus, which subsists on a diet comprising amphipods, algae, small fish, shrimp, crabs, and other such organisms [55], the cultured population is supplied with feed formulations that are characterized by comparatively elevated protein contents and a substantial amino acid profile. Therefore, the notable augmentation of Escherichia-Shigella within the cultured population may be implicated in facilitating protein utilization processes. Hosts may selectively acquire suitable environmental bacteria through cell surface recognition and adhesion mechanisms [56], a result of long-term ecological adaptation between the host and microbiota, which is crucial for host health [57]. For instance, the Enterococcus genus, which exhibits high abundance in cultured populations, has demonstrated its capacity to stimulate fish growth, regulate the intestinal microbiota in order to inhibit inflammatory responses, and augment the immune system [58,59]. The restricted quantity of the annotated species documented in our investigation can be ascribed to a confluence of objective impediments and the intrinsic limitations of the sequencing technology utilized.
In the intestinal tracts of both wild and cultured O. fasciatus, the high abundance of diverse microorganisms highlights their crucial roles in facilitating the host’s adaptation to various ecological niches. Specifically, Photobacterium leiognathi, a photoheterotrophic bacterium, not only augments nutrient metabolism but also bolsters immune function [52,53]. Conversely, the cold- and pressure-resilient species Psychrobacter cibarius and Psychrobacter maritimus likely enhance the host’s tolerance to extreme conditions by participating in metabolic processes [60]. Additionally, Shewanella marina, a facultative anaerobe, elevates the host’s nutrient absorption efficiency through its versatile metabolic pathways [61]. In cultured settings, the elevated abundance of Flavonifractor plautii, Lactococcus taiwanensis, and Bacteroides plebeius, which is closely linked to the farming environment and feed composition, may positively influence the host’s growth and development via their involvement in metabolic activities [62,63,64]. These microbial species, through their distinct mechanisms of action, collectively contribute to the maintenance of striped seabream health and underscore the potential for refining aquaculture management strategies through the modulation of intestinal microbial community composition. In particular, objective factors exert a substantial impact. Numerous species have not yet been isolated and cultivated, posing an obstacle to their accurate identification and annotation through sequence analysis. Moreover, the deficiencies in the completeness of existing databases exacerbate this challenge, as vital species-related information may be lacking or still awaiting incorporation.
Gut microbiota diversity is vital for maintaining the stability of the host’s gut microecology and is closely linked to host health and disease resistance [29,65]. BugBase phenotype predictions revealed that the gut microbiota of wild O. fasciatus exhibits higher potential pathogenicity and biofilm formation capabilities. This may be due to the diversity and complexity of microorganisms in the natural environment or an adaptive response to variable environmental conditions. Specifically, the higher abundance of pathogenic bacteria such as Pseudomonas and Vibrio in natural populations increases the risk of host infection. This observation may be associated with the high organic matter content in coastal waters and the subsequent water pollution in these areas, which promote the growth and proliferation of pathogenic bacteria [66]. In contrast, the cultured population, living in a stable rearing environment, exhibited lower pathogenicity and biofilm formation potential in their gut microbiota. A higher alpha diversity index indicates greater bacterial community stability and stronger disease resistance, which benefits fish health [37,67]. Thus, our gut microbiota diversity analysis suggests better health in the cultured population. It is noteworthy that the colonization of various bacterial types, including pathogenic bacteria [68] and probiotics, within the gut is a normal occurrence. Under normal circumstances, pathogenic bacteria coexist harmlessly within the gut [69], while opportunistic pathogens only cause disease under specific conditions, such as immune or physiological stress in the host [70].

5. Conclusions

In summary, this study revealed significant differences in the composition and function of gut microbiota between wild and cultured O. fasciatus populations, reflecting the distinct environments and dietary habits of the two populations. These differences may influence the populations’ health and physiological functions. Future research should further investigate how these variations affect the growth, immunity, and disease resistance of O. fasciatus, aiming to provide a scientific basis for improved farming management of this species. Importantly, our findings suggest that substantial enhancements in aquaculture practices and fish health management can be attained through strategic measures such as optimizing feed formulations, tailoring aquaculture environments to mimic beneficial natural conditions, regulating pivotal microbial populations, ensuring adequate intake of polyunsaturated fatty acids (PUFAs), and reducing the risk of disease infection.

Author Contributions

Conceptualization, K.Z. and H.W.; data curation, K.Z.; writing—original draft, K.Z. and H.W.; writing—review and editing, S.Z. and K.X. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Zhejiang Provincial Natural Science Foundation of China under grant number LGN21C190005, and the Key Technology and System Exploration of Quota Fishing, Ministry of Agriculture and Rural Affairs Agricultural Finance of China, grant number 36, 2017.

Institutional Review Board Statement

The studies of Oplegnathus fasciatus received approval from Zhejiang Ocean University’s Committee on the Ethics of Animal Experiments (approval number: ZJOU-AQU-2022-090, approved on 15 April 2022).

Informed Consent Statement

All authors have read and agreed to the published version of the manuscript.

Data Availability Statement

The datasets that support the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgments

We thank the staff members of the Scientific Observing and Experimental Station of Fishery Resources for Key Fishing Grounds, Ministry of Agriculture, Marine Fisheries Research Institute of Zhejiang for providing assistances in the laboratory. We are also grateful to all the reviewers for their valuable comments and advice.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Map of the sampling areas for wild and cultured Oplegnathus fasciatus.
Figure 1. Map of the sampling areas for wild and cultured Oplegnathus fasciatus.
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Figure 2. Statistical analysis of alpha diversity for gut microbiota in wild and cultured striped knifejaw (Oplegnathus fasciatus) populations.
Figure 2. Statistical analysis of alpha diversity for gut microbiota in wild and cultured striped knifejaw (Oplegnathus fasciatus) populations.
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Figure 3. Heatmap illustrating the differential gut microbial taxa at the phylum level between wild (W1–W16) and cultured (C1–C39) striped knifejaw (Oplegnathus fasciatus) populations.
Figure 3. Heatmap illustrating the differential gut microbial taxa at the phylum level between wild (W1–W16) and cultured (C1–C39) striped knifejaw (Oplegnathus fasciatus) populations.
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Figure 4. Heatmap illustrating the differential gut microbial taxa at the family level between wild and cultured striped knifejaw (Oplegnathus fasciatus) populations.
Figure 4. Heatmap illustrating the differential gut microbial taxa at the family level between wild and cultured striped knifejaw (Oplegnathus fasciatus) populations.
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Figure 5. Heatmap illustrating the differential gut microbial taxa at the genus level between wild and cultured striped knifejaw (Oplegnathus fasciatus) populations.
Figure 5. Heatmap illustrating the differential gut microbial taxa at the genus level between wild and cultured striped knifejaw (Oplegnathus fasciatus) populations.
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Figure 6. Nonmetric multidimensional scaling (NMDS) analysis of beta diversity in the gut microbiota of wild and cultured striped knifejaws (Oplegnathus fasciatus) at the species level.
Figure 6. Nonmetric multidimensional scaling (NMDS) analysis of beta diversity in the gut microbiota of wild and cultured striped knifejaws (Oplegnathus fasciatus) at the species level.
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Figure 7. Enrichment of KEGG pathways associated with striped knifejaw (Oplegnathus fasciatus) intestinal microbiota genes.
Figure 7. Enrichment of KEGG pathways associated with striped knifejaw (Oplegnathus fasciatus) intestinal microbiota genes.
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Figure 8. Differences in test results regarding the abundance data of two secondary classifications.
Figure 8. Differences in test results regarding the abundance data of two secondary classifications.
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Figure 9. Phenotype predictions of gut microbiota in wild and cultured striped knifejaw (Oplegnathus fasciatus) populations.
Figure 9. Phenotype predictions of gut microbiota in wild and cultured striped knifejaw (Oplegnathus fasciatus) populations.
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Table 1. Composition and characteristics of the two sampled striped knifejaw (Oplegnathus fasciatus) populations.
Table 1. Composition and characteristics of the two sampled striped knifejaw (Oplegnathus fasciatus) populations.
PopulationSample CountBody Length (mm)Mean Body Length (mm)Body Weight (g)Mean Body Weight (g)
AllWild10096–143124 ± 843.9–138.386.4 ± 17.5
Cultured7488–141108 ± 1424.5–112.052.4 ± 17.7
Gut MicrobiotaWild1698–121114 ± 637.9–83.567.7 ± 12.4
Cultured3988–119100 ± 1024.8–73.344.9 ± 16.8
Table 2. Average relative abundance of intestinal microbiota at the phylum level in wild and cultured Oplegnathus fasciatus populations.
Table 2. Average relative abundance of intestinal microbiota at the phylum level in wild and cultured Oplegnathus fasciatus populations.
PhylumWildCulturedp-Valueq-Value
Pseudomonadota0.86290.2847<0.010.00194
Bacillota0.09020.2142<0.010.01368
Verrucomicrobiota0.00100.2381<0.010.00194
Chloroflexota0.00160.0567<0.010.00194
Actinomycetota0.00800.0249<0.010.00194
Acidobacteriota0.00190.0249<0.010.00194
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Zhu, K.; Zhang, S.; Xu, K.; Wang, H. Structural Analysis and Functional Prediction of Gut Microbiota in Wild and Cultured Striped Knifejaw (Oplegnathus fasciatus). J. Mar. Sci. Eng. 2024, 12, 2275. https://doi.org/10.3390/jmse12122275

AMA Style

Zhu K, Zhang S, Xu K, Wang H. Structural Analysis and Functional Prediction of Gut Microbiota in Wild and Cultured Striped Knifejaw (Oplegnathus fasciatus). Journal of Marine Science and Engineering. 2024; 12(12):2275. https://doi.org/10.3390/jmse12122275

Chicago/Turabian Style

Zhu, Kai, Susu Zhang, Kaida Xu, and Haozhan Wang. 2024. "Structural Analysis and Functional Prediction of Gut Microbiota in Wild and Cultured Striped Knifejaw (Oplegnathus fasciatus)" Journal of Marine Science and Engineering 12, no. 12: 2275. https://doi.org/10.3390/jmse12122275

APA Style

Zhu, K., Zhang, S., Xu, K., & Wang, H. (2024). Structural Analysis and Functional Prediction of Gut Microbiota in Wild and Cultured Striped Knifejaw (Oplegnathus fasciatus). Journal of Marine Science and Engineering, 12(12), 2275. https://doi.org/10.3390/jmse12122275

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